Design and Implement of Personalize Meta-Search Engine Based on FCA

Juan, Tang; Du, Yajun; Wang, Keliang

doi:10.1109/icmlc.2007.4370850

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…They used to be a viable instrument for retrieving data from the tremendous data archive. Case in point, Google, which is one of the prominent web crawlers, not just gives fitting indexed lists to the client on the planet by pack up of more than 20 hundred millions website pages, additionally an ideal opportunity to hunt is not generally past 0.5 second [2]. The pervasiveness of the Internet and Web has prompted the rise of a few web indexes with changing capabilities.…”

Section: Introductionmentioning

confidence: 99%

Web Personalization using the Efficient Fuzzy Cluster Based Multi Objective Social Spider Algorithm

Rao¹,

Vasumathi²

2016

ijastems

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Big data is a fast growing technology in addition to the initial stage of development in big data. Two different kinds of computing areas we have batch computing and stream computing. But it should not satisfying all the aspects like energy efficiency, resource allocation time, and there is no proper scheduling algorithm for faster resource allocation in this paper, especially we discuss with a comparative study of energy bargain techniques has been made in the big data environment which comprises two computing areas like Batch Computing and stream computing. In this context, a special attention has been made to focus on techniques which achieve higher energy efficiency and lower response time. And we provide mathematical relations to evaluating the performance time of a task, and energy efficiency In Existing scenario, Suitable methods will be proposed sort out the issues associated with Big Data Environment. In this paper applying controls and resource scheduling techniques for Big Data platforms to improve performance.

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Section: Introductionmentioning

confidence: 99%